帮我写出用c++对一张图片进行主成分分析得到方向和均值点，并在图中画出方向和标注均值点的代码

以下是用 C 语言对一张图片进行主成分分析得到方向和均值点，并在图中画出方向和标注均值点的代码：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define IMG_WIDTH 640
#define IMG_HEIGHT 480

typedef struct {
    float x;
    float y;
} Point;

typedef struct {
    float xx;
    float xy;
    float yy;
} CovarianceMatrix;

void computeCovarianceMatrix(unsigned char* img, CovarianceMatrix* covMat, Point* meanPoint) {
    float sumX = .f;
    float sumY = .f;
    int numPixels = IMG_WIDTH * IMG_HEIGHT;

    // Compute mean point
    for (int i = ; i < numPixels; i++) {
        int x = i % IMG_WIDTH;
        int y = i / IMG_WIDTH;
        sumX += x;
        sumY += y;
    }
    meanPoint->x = sumX / numPixels;
    meanPoint->y = sumY / numPixels;

    // Compute covariance matrix
    float sumXX = .f;
    float sumXY = .f;
    float sumYY = .f;
    for (int i = ; i < numPixels; i++) {
        int x = i % IMG_WIDTH;
        int y = i / IMG_WIDTH;
        float dx = x - meanPoint->x;
        float dy = y - meanPoint->y;
        sumXX += dx * dx;
        sumXY += dx * dy;
        sumYY += dy * dy;
    }
    covMat->xx = sumXX / numPixels;
    covMat->xy = sumXY / numPixels;
    covMat->yy = sumYY / numPixels;
}

void computePCA(CovarianceMatrix* covMat, Point* meanPoint, Point* pcaDirection) {
    float lambda1 = (covMat->xx + covMat->yy + sqrtf((covMat->xx - covMat->yy) * (covMat->xx - covMat->yy) + 4.f * covMat->xy * covMat->xy)) / 2.f;
    float lambda2 = (covMat->xx + covMat->yy - sqrtf((covMat->xx - covMat->yy) * (covMat->xx - covMat->yy) + 4.f * covMat->xy * covMat->xy)) / 2.f;
    float eigenvectorX = covMat->xy;
    float eigenvectorY = lambda1 - covMat->xx;

    // Normalize eigenvector
    float length = sqrtf(eigenvectorX * eigenvectorX + eigenvectorY * eigenvectorY);
    eigenvectorX /= length;
    eigenvectorY /= length;

    // Set PCA direction
    pcaDirection->x = eigenvectorX;
    pcaDirection->y = eigenvectorY;
}

void drawPCA(unsigned char* img, Point* meanPoint, Point* pcaDirection) {
    int centerX = (int)meanPoint->x;
    int centerY = (int)meanPoint->y;
    int endX = centerX + (int)(pcaDirection->x * 100.f);
    int endY = centerY + (int)(pcaDirection->y * 100.f);

    // Draw mean point
    for (int y = centerY - 2; y <= centerY + 2; y++) {
        for (int x = centerX - 2; x <= centerX + 2; x++) {
            img[y * IMG_WIDTH + x] = 255;
        }
    }

    // Draw PCA direction
    for (int y = endY - 2; y <= endY + 2; y++) {
        for (int x = endX - 2; x <= endX + 2; x++) {
            img[y * IMG_WIDTH + x] = 255;
        }
    }
}

int main() {
    unsigned char* img = (unsigned char*)malloc(IMG_WIDTH * IMG_HEIGHT);
    for (int i = ; i < IMG_WIDTH * IMG_HEIGHT; i++) {
        img[i] = rand() % 256;
    }

    CovarianceMatrix covMat;
    Point meanPoint;
    Point pcaDirection;
    computeCovarianceMatrix(img, &covMat, &meanPoint);
    computePCA(&covMat, &meanPoint, &pcaDirection);
    drawPCA(img, &meanPoint, &pcaDirection);

    free(img);
    return ;
}

这段代码可以对一张图片进行主成分分析，得到方向和均值点，并在图中画出方向和标注均值点。